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      Everyday bat vocalizations contain information about emitter, addressee, context, and behavior

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      Scientific Reports
      Nature Publishing Group

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          Abstract

          Animal vocal communication is often diverse and structured. Yet, the information concealed in animal vocalizations remains elusive. Several studies have shown that animal calls convey information about their emitter and the context. Often, these studies focus on specific types of calls, as it is rarely possible to probe an entire vocal repertoire at once. In this study, we continuously monitored Egyptian fruit bats for months, recording audio and video around-the-clock. We analyzed almost 15,000 vocalizations, which accompanied the everyday interactions of the bats, and were all directed toward specific individuals, rather than broadcast. We found that bat vocalizations carry ample information about the identity of the emitter, the context of the call, the behavioral response to the call, and even the call’s addressee. Our results underline the importance of studying the mundane, pairwise, directed, vocal interactions of animals.

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          Most cited references40

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          Speaker Verification Using Adapted Gaussian Mixture Models

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            Speech recognition with primarily temporal cues.

            Nearly perfect speech recognition was observed under conditions of greatly reduced spectral information. Temporal envelopes of speech were extracted from broad frequency bands and were used to modulate noises of the same bandwidths. This manipulation preserved temporal envelope cues in each band but restricted the listener to severely degraded information on the distribution of spectral energy. The identification of consonants, vowels, and words in simple sentences improved markedly as the number of bands increased; high speech recognition performance was obtained with only three bands of modulated noise. Thus, the presentation of a dynamic temporal pattern in only a few broad spectral regions is sufficient for the recognition of speech.
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              Allometry of alarm calls: black-capped chickadees encode information about predator size.

              Many animals produce alarm signals when they detect a potential predator, but we still know little about the information contained in these signals. Using presentations of 15 species of live predators, we show that acoustic features of the mobbing calls of black-capped chickadees (Poecile atricapilla) vary with the size of the predator. Companion playback experiments revealed that chickadees detect this information and that the intensity of mobbing behavior is related to the size and threat of the potential predator. This study demonstrates an unsuspected level of complexity and sophistication in avian alarm calls.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                22 December 2016
                2016
                : 6
                : 39419
                Affiliations
                [1 ]Department of Zoology, Faculty of Life sciences, Tel Aviv University , Tel Aviv, Israel
                Author notes
                Article
                srep39419
                10.1038/srep39419
                5178335
                28005079
                c1e75159-fab0-4759-adf6-5d3e70c14b07
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 31 August 2016
                : 22 November 2016
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